Real-time Reflection Research Articles

Microwave Thermal Ablation of Thyroid Nodules with the MONTREAL Technique: Preliminary Clinical Results.

Ultrasound-guided percutaneous Microwave Thermoablation (MWA) is an increasingly popular minimally invasive therapy for the treatment of benign thyroid nodules due to its remarkable heating velocity and resilience to heat sinking. We present a cohort of 26 patients (17 F, 9M, mean age 56.2yy) with 20 goiters (mean volume 34.9cc, min 6.5cc-max 84cc) and 6 autonomously functioning nodules (AFTNs, mean volume 11.6cc, min 3.5cc-max 24cc) treated with MWA, using the moving shot technique and a novel energy delivery algorithm (MONTREAL), based on intra-operative real-time reflectivity measurements: each moving shot was automatically terminated when reflectivity was observed to ramp up. 17G or 18G internally cooled 2.45 GHz applicators were used (AMICA-PROBE, HS HOSPITAL SERVICE SpA), operated at 15-30W. On average, each treatment deposited 9.9±5.5kJ during 696±325s, through 26.7±14.4 moving shots: the mean moving shot duration was 28.1±9.0s, yielding a mean ablation time per unit nodule volume of 34.3±19.1s/cc. No mild nor severe complications were recorded. Post-MWA ultrasound follow-up showed a mean volume reduction ratio of 59.1±10.2% [min 44% - max 80%] at 3 months and of 70.1±8.5% [min 53% - max 91%] at 6 months, with slightly better outcomes in the AFTNs sub-group (volume reduction of 65.3±10.2%/76.0±4.0% at 3/6 months and, in all cases, normal TSH values at 3 months upon pharmacological therapy suspension). MWA treatments of benign nodules with the MONTREAL technique appeared to be safe, fast, and effective. Further research is warranted to confirm these preliminary results.

The Injury Progression in Acute Blast-Induced Mild Traumatic Brain Injury in Rats Reflected by Diffusion Tensor Imaging and Immunohistochemical Examination.

Diffusion tensor imaging (DTI) has emerged as a promising neuroimaging tool for detecting blast-induced mild traumatic brain injury (bmTBI). However, lack of refined acute-phase monitoring and reliable imaging biomarkers hindered its clinical application in early diagnosis of bmTBI, leading to potential long-term disability of patients. In this study, we used DTI in a rat model of bmTBI generated by exposing to single lateral blast waves (151.16 and 349.75 kPa, lasting 47.48 ms) released in a confined bioshock tube, to investigate whole-brain DTI changes at 1, 3, and 7 days after injury. Combined assessment of immunohistochemical analysis, transmission electron microscopy, and behavioral readouts allowed for linking DTI changes to synchronous cellular damages and identifying stable imaging biomarkers. The corpus callosum (CC) and brainstem were identified as predominantly affected regions, in which reduced fractional anisotropy (FA) was detected as early as the first day after injury, with a maximum decline occurring at 3 days post-injury before returning to near normal levels by 7 days. Axial diffusivity (AD) values within the CC and brainstem also significantly reduced at 3 days post-injury. In contrast, the radial diffusivity (RD) in the CC showed acute elevation, peaking at 3 days after injury before normalizing by the 7-day time point. Damages to nerve fibers, including demyelination and axonal degeneration, progressed in lines with changes in DTI parameters, supporting a real-time macroscopic reflection of microscopic neuronal fiber injury by DTI. The most sensitive biomarker was identified as a decrease in FA, AD, and an increase in RD within the CC on the third day after injury, supporting the diagnostic utility of DTI in cases of bmTBI in the acute phase.

Correction of microwave pulse reflection by digital filters in superconducting quantum circuits

Abstract Reducing the control error is vital for high-fidelity digital and analog quantum operations. In superconducting circuits, one disagreeable error arises from the reflection of microwave signals due to impedance mismatch in the control chain. Here, we demonstrate a reflection cancelation method when considering that there are two reflection nodes on the control line. We propose to generate the pre-distortion pulse by passing the envelopes of the microwave signal through digital filters, which enables real-time reflection correction when integrated into the field-programmable gate array (FPGA). We achieve a reduction of single-qubit gate infidelity from 0.67% to 0.11% after eliminating microwave reflection. Real-time correction of microwave reflection paves the way for precise control and manipulation of the qubit state and would ultimately enhance the performance of algorithms and simulations executed on quantum processors.

Marketing Strategy 5.0 on Live Streaming Commerce Tiktok

This research explores the role of live streaming features in marketing strategy in the context of Marketing Strategy 5.0 and e-commerce live streaming. Using a qualitative phenomenological approach involving direct observation and secondary data analysis, this research identifies how live streaming not only functions as a tool to facilitate real-time product reflection, but also as a platform to build in-depth interactions with customers. Through the Marketing Strategy 5.0 approach, which emphasizes the use of technology to improve customer experience and personalization, the research focus is the TikTok account @serbagroosir with the consideration: this company has survived for more than 5 years with sales always increasing. Through the data analysis technique used, Manual Data Analysis Procedure (MDAP), from the results of interviews accompanied by triangulation of sources and theory, this research found that TikTok's live streaming feature allows companies to answer consumer questions directly, provide exclusive promotions, and encourage impulse purchases. Additionally, live streaming helps in forming a loyal customer community and expands market reach thanks to TikTok's algorithm that supports the discovery of new content. This research suggests that companies should increase the frequency of live streaming sessions and leverage data analytics to optimize streaming timing and content. For future researchers, it is recommended to expand the scope of the study by involving multiple accounts and platforms as well as conducting in-depth analysis of consumer behavior during live streaming sessions to provide more comprehensive insight into the effectiveness of this strategy in e-commerce.

A light/thermal cascaded-driven equipment for machine recognition inspired by water lilies using as multifunctional soft actuator

Inspired by the natural stimulus–response of plants and animals, a range of soft equipment has been extensively developed and used in intelligent human–computer interaction, editable remote drives, and machine learning. Poly(N-isopropyl acrylamide) (PNIPAM) hydrogels have gained popularity thanks to their low phase transition temperature and excellent flexibility. However, the PNIPAM hydrogels suffer from poor mechanical properties, low electrical conductivity, and lack of self-responsiveness. Herein, a bilayer light/thermal cascaded-driven anisotropic poly acrylamide/poly(N-isopropylacrylamide-co-acrylamide)-polyvinyl alcohol-MXene (P/PP-M) actuator was prepared by a simple two-step polymerization method. The unique bionic light/thermal response mechanism enables rapid conversion of energy forms and the construction of remote editable actuators. Concretely, the mechanical properties of hydrogels (strain: 1014 %, stress: 94 KPa) have been greatly improved by copolymerizing MXene nanosheets and multiplex hydrogels through two-by-two interpenetrating molecular chains. MXene nanosheets formed dynamic networks conferring the hydrogel system with high conductivity and light/thermal conversion efficiency. The P/PP-M soft actuator features high sensitivity (Gauge factor = 3.62), fast response time (400 ms), and cycling durability (>500 cycles). Finally, the energy transfer mechanism from light to thermal energy to kinetic energy was corroborated by preparing a series of bionic equipment. Manual clips were prepared on this basis, which enables the transportation of objects and realizes the real-time reflection of the operating status of remotely driven soft manual clips through changes in electrical signals. Thus, the proposed efficient editable remote-driven machine recognition soft equipment provides new insights for developing intelligent flexible robots and wearable smart devices.

Integrated LSPR Biosensing Signal Processing Strategy and Visualization Implementation.

The LSPR biosensor chip is a groundbreaking tool popular in laboratory settings for identifying disease markers. However, its use in clinical environments is not as widespread. One notable gap is the lack of a universal signal processing tool for LSPR biosensing. To escalate its precision, there is an emerging need for software that not only optimizes signal processing but also incorporates self-verification functionalities within LSPR biochemical sensors. Enter the visual LSPR sensor software-an innovative platform that processes real-time transmission or reflection spectra. This advanced software adeptly captures the nuanced structural changes at the nanostructure interface prompted by environmental fluctuations. It diligently records and computes a suite of parameters, including the resonance wavelength shift, full width at half maximum, sensitivity, and quality factor. These features empower users to tailor processing algorithms for each data capture session. Transcending traditional instruments, this method accommodates a multitude of parameters and ensures robust result validation while tactfully navigating nanostructure morphology complexities. Forsaking third-party tool dependencies, the software tackles challenges of precision and cost-effectiveness head-on, heralding a significant leap forward in nanophotonics, especially for high-throughput LSPR biosensing applications. This user-centric innovation marks substantial progress in biochemical detection. It is designed to serve both researchers and practitioners in the field of nanophotonic sensing technology, simplifying complexity while enhancing reliability and efficiency.

Virtual Reality and Internet of Things Based Digital Twin for Smart City Cross-Domain Interoperability

The fusion of Internet of Things (IoT), Digital Twins, and Virtual Reality (VR) technologies marks a pivotal advancement in urban development, offering new services to citizens and municipalities in urban environments. This integration promises enhanced urban planning, management, and engagement by providing a comprehensive, real-time digital reflection of the city, enriched with immersive experiences and interactive capabilities. It enables smarter decision-making, efficient resource management, and personalized citizen services, transforming the urban landscape into a more sustainable, livable, and responsive environment. The research presented herein focuses on the practical implementation of a DT concept for managing cross-domain smart city services, leveraging VR technology to create a virtual replica of the urban environment and IoT devices. Imperative for cross-domain city services is interoperability, which is crucial not only for the seamless operation of these advanced tools but also for unlocking the potential of cross-service applications. Through the deployment of our model at the IoTMADLab facilities, we showcase the integration of IoT devices within varied urban infrastructures. The outcomes demonstrate the efficacy of VR interfaces in simplifying complex interactions, offering pivotal insights into device functionality, and enabling informed decision-making processes.

Freezing-mediated formation of supraproteins using depletion forces

HypothesisLong-acting formulations such as microparticles, injectable depots and implantable devices can realize spatiotemporally controlled delivery of protein drugs to extend their therapeutic in vivo half-lives. To efficiently encapsulate the protein drugs into such drug delivery systems, (sub)micron-sized protein particles are needed. The formation of micronized supraproteins can be induced through the synergistic combination of attractive depletion forces and freezing. The size of the supraproteins can be fine-tuned from submicron to several microns by adjusting the ice crystallization rate through the freeze-quench depth, which is set by the target temperature.MethodsSupraprotein micron structures were prepared from protein solutions under various conditions in the presence and absence of nonadsorbing polyethylene glycol. Scanning electron microscopy and dynamic light scattering were employed to determine the sizes of the supraproteins and real-time total internal reflection fluorescent microscopy was used to follow the supraprotein formation during freezing. The protein secondary structure was measured before and after micronization by circular dichroism. A phase diagram of a protein–polyethylene glycol mixture was theoretically predicted to investigate whether the depletion interaction can elucidate the phase behavior.FindingsMicronized protein supraparticles could be prepared in a controlled manner by rapid freeze-drying of aqueous mixtures of bovine serum albumin, horseradish peroxidase and lysozyme mixed with polyethylene glycol. Upon freezing, the temperature quench initiates a phase separation process which is reminiscent of spinodal decomposition. This demixing is subsequently arrested during droplet phase separation to form protein-rich microstructures. The final size of the generated protein microparticles is determined by a competition between phase separation and cooling rate, which can be controlled by target temperature. The experimental phase diagram of the aqueous protein–polyethylene glycol dispersion aligns with predictions from depletion theory for charged colloids and nonadsorbing polymers.

A new method of dynamic network security analysis based on dynamic uncertain causality graph

In the context of cloud computing, network attackers usually exhibit complex, dynamic, and diverse behavior characteristics. Existing research methods, such as Bayesian attack graphs, lack evidence correlation and real-time reflection of the network attack events, and high computational complexity for attack analysis. To solve these problems, this study proposes a Dynamic Uncertain Causal Attack Graph (DUCAG) model and a Causal Chain-based Risk Probability Calculation (CCRP) algorithm. The DUCAG model is constructed to represent the uncertain underlying causalities among network attack events, and the CCRP algorithm aims at dynamically updating the causality weights among different network attack events and attacker hypotheses based on alarm information and causal chain reasoning process. By causality simplification and causality reasoning methods, the CCRP efficiently predicts the attacker behaviors and potential attack likelihood under uncertain time-varying attack situations, and is robust to the incompleteness and redundancy in alarm information. Four experiments under different attack scenarios demonstrate that, the DUCAG model can effectively characterize and predict the complex and uncertain attack causalities, in a manner of high time efficiency. The proposed method has application significance on cloud computing platforms by dynamically evaluating network security status, predicting the future behaviors of attackers, and assisting in adjusting network defense strategies.

Point Cloud-Based Spatial Environment Development for Near Real-Time Erection Simulation in Shipyards

<i>Interference and collisions often occur in the loading process at shipyards. Existing simulation methods focus primarily on resource processes and schedules, and there is a lack of real-time reflection in the complex and highly variable loading process. This study aims to develop a spatial environment incorporating real-time product data, such as hulls, and confirms its effectiveness by simulating various construction scenarios. As a method, a near real-time spatial environment based on broadband laser scanning was established, with the situation of loading heavy cargo assumed when converting an existing ship into an LNG dual-fuel propulsion ship. A case study simulation of near-real-time cargo loading processes was then conducted using Unity 3D to confirm the interference and collision risks within the spatial environment. The results indicated that interference occurred in structures previously not identified in the design data, and a collision occurred during the loading object erection phase. The simulation confirmed that the identification of interference and collision risks during the erection phase highlights the need for a relocation or removal process of potential hazards before erection takes place. An improved erection simulation that integrates near real-time data could effectively prevent interference and collision risks.</i>

Metacognition and diagrams in marking-for-self

AbstractMetacognition relies on representations, which are commonly viewed as internal knowledge structures. We explore the idea that external embodied diagrams, rather than monomodal symbolic-based entities, can provide an accurate description of metacognition in choreographic dance. When marking, dancers use their bodies to represent properties, dynamics, or structures of dance phrases. Marking-for-self occurs when a dancer marks the dance in their own unique manner, potentially allowing for real-time reflection through the manipulation of external signs. These manipulations can be considered diagrammatic semiosis, as diagrams signify shared relational parts analogous to the parts of their objects. Based on Peirce’s semiotics, we argue that semiosis is crucial for metacognition. This paper is structured to first review marking and marking-for-self, followed by an overview of metacognition. We then define marking-for-self as a metacognitive phenomenon and introduce Peirce’s concept of semiosis and diagrams. Finally, we describe marking as a diagrammatic sign and explain how marking-for-self is an embodied metacognitive process achieved through the manipulation of diagrammatic structures.

The Integrin Adaptor Kindlin-3 Is a Gatekeeper for Germinal Center Responses and the Development of Chronic Lymphocytic Leukemia

Background: High affinity antibody production occurs in the germinal centers (GCs), which are segregated into a dark zone (DZ) and a light zone (LZ). GC B cells proliferate in the DZ and encounter follicular dendritic cells in the LZ. Cell trafficking between the two zones is regulated by CXCR4 (DZ) and CXCR5 (LZ) signaling. Integrins may regulate B cell positioning and B cell immune synapse formation. Recently, we have shown that the integrin adaptor kindlin-3 is not only required for integrin activation in B cells, but unexpectedly also acts as a brake on CXCR5 responsiveness. Kindlin-3 thereby prevents B cell hyperactivation and differentiation into GC-like B cells in absence of antigen. 1 Here we investigate the impact of kindlin-3 on GC responses upon antigen challenging and on malignant transformation. Methods: We developed a B cell-specific knockout mouse model (mb1Cre Fermt3fl/fl (K3ΔB)) in which kindlin-3 ( Fermt3) was knocked out in all B cells. K3ΔB and control wild-type (WT) mice were challenged with sheep red blood cells (SRBC). GC formation and immunoglobulin (Ig) production were analyzed by flow cytometry. Ex vivo B cell proliferation and Ig class switching formation assays were performed. We investigated the immune synapse formation of WT and kindlin-3-deficient B cells using a biomimetic model involving a planar artificial lipid bilayer containing GPI-linked integrin ligands and bound fluorescently labeled surrogate antigens. The formation of immune synapse and central antigen aggregation in the immune synapse were analyzed by real-time interference reflection microscopy and laser scanning confocal microscopy. To investigate the contribution of kindlin-3 in a model of mature B cell malignancy, we used TCL1 transgenic (TCL1) mice resembling chronic lymphocytic leukemia (CLL) to generate the mb1Cre Fermt3fl/fl Tcl1 (TCL1-K3ΔB) mouse model. Tumor burden in TCL1-K3ΔB and TCL1 control mice was monitored by flow cytometry over time and at sacrifice using CD19/CD5 antibodies. B cell receptor (BCR) signaling of CLL cells was analyzed using Phosphoflow. Results: K3∆B mice immunized with SRBC exhibited defective GC responses (30% reduction in GC-B cells compared to WT) and antibody production (49% reduction in SRBC-specific IgG2b production in serum compared to WT) on day 7 after immunization. Ex vivo, kindlin-3-deficient B cells were unable to form immune synapses (Figure 1A), to proliferate, and to switch antibody classes. The tumors in TCL1 mice started in the peritoneal cavity and subsequently spread to the spleen, blood and bone marrow. TCL1-K3ΔB mice presented with an almost complete abolished leukemia onset in the peritoneal cavity (92% less tumor burden in TCL1-K3ΔB compared to control TCL1 mice) in 4-month-old mice (Figure 1B i). Moreover, tumor burden in blood (Figure 1B ii), spleen, and bone marrow (Figure 1B iii) was strongly reduced at the late stage of disease (11.5-month-old mice), with an 82% lower tumor burden in spleen and a 90% lower tumor burden in bone marrow of TCL1-K3ΔB mice compared to TCL1 control mice. In addition, kindlin-3-deficient CLL cells exhibited impaired phosphoAkt and phosphoSyk signaling upon BCR engagement. Summary/Conclusion: In summary, kindlin-3 maintains the balance between a state of B cell homeostasis and an effective antigenic response by acting as a gatekeeper of GC formation, and is substantial for leukemic onset in CLL. Reference: 1. Härzschel A, Li L, Krenn PW, et al. Kindlin-3 maintains marginal zone B cells but confines follicular B cell activation and differentiation. J Leukoc Biol. 2022 Apr;111(4):745-758.

Research on a Method for Online Damage Evaluation of Turbine Blades in a Gas Turbine Based on Operating Conditions

Performing online damage evaluation of blades subjected to complex cyclic loads based on the operating state of a gas turbine enables real-time reflection of a blade’s damage condition. This, in turn, facilitates the achievement of predictive maintenance objectives, enhancing the economic and operational stability of gas turbine operations. This study establishes a hybrid model for online damage evaluation of gas turbine blades based on their operational state. The model comprises a gas turbine performance model based on thermodynamic simulation, a component load calculation model based on a surrogate model, an updated cycle counting method based on four-point rainflow, and an improved damage mechanism evaluation model. In the new model, the use of a surrogate model for the estimation of blade loading information based on gas turbine operating parameters replaces the conventional physical modeling methods. This substitution enhances the accuracy of blade loading calculations while ensuring real-time performance. Additionally, the new model introduces an updated cycle counting method based on four-point rainflow and an improved damage mechanism evaluation model. In the temperature counting part, a characteristic stress that represents the stress information during the cyclic process is proposed. This inclusion allows for the consideration of the impact of stress fluctuations on creep damage, thereby enhancing the accuracy of the fatigue damage assessment. In the stress counting part, the model incorporates time information associated with each cycle. This concept is subsequently applied in determining the identified cyclic strain information, thereby improving the accuracy of the fatigue damage evaluation. Finally, this study applies the new model to an online damage evaluation of a turbine stationary blade using actual operating data from a micro gas turbine. The results obtained from the new model are compared with the EOH recommended by the OEM, validating the accuracy and applicability of the new model.

An Online Fatigue Damage Evaluation Method for Gas Turbine Hot Components

The failure of gas turbines’ hot components due to fatigue significantly affects their efficient and stable operation. Conducting online damage assessment of components subjected to complex cyclic loads based on the working conditions of gas turbines can provide real-time reflection of component fatigue damage and achieve the purpose of predictive maintenance. In this study, we propose an online cycle counting method that considers temperature fluctuations during the cycle process. Our method is based on the four-point online rainflow counting method by coupling the counting variable with time, introducing the concept of the duration time for full cycles and half cycles, and incorporating a characteristic temperature that better represents the temperature information during the cycle process. With reference to the characteristic temperature, our proposed method comprehensively considers the form and parameters of subsequent life assessment models. This paper provides a detailed explanation of the proposed method and applies it to the fatigue damage assessment of turbine vanes in a micro gas turbine, thereby verifying its accuracy and applicability.

The prospect and challenge of liquid biopsy in the diagnosis and treatment of chest malignancy

In recent years, the incidence of chest malignant tumors in China has increased year by year, which has seriously threatened the health problems of people. Among them, early screening and intervention of patients with chest malignancies is the key to cancer prevention. Early detection, early diagnosis, and early treatment as the "three early prevention" of clinical practice are conducive to improve the survival rate of tumor patients. As a non-invasive and real-time reflection of tumor status, liquid biopsy has gradually received attention in clinical diagnosis and treatment. Circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and exosomes as liquid biopsy "Three carriages" are not only widely used in the diagnosis, monitoring and prognostic evaluation of chest malignancies, but also face many unknown challenges. In this article, the application of liquid biopsy in chest malignancies in recent years is elaborated in detail, which provides a reference for the formulation of clinical tumor prevention and diagnosis and treatment strategies.

EDEN (Electrocardiographic Radial Depth Navigation): A Novel Approach to Navigate Inside Heart Muscle

BackgroundIntramyocardial guidewire navigation is a novel technique that allows free transcatheter movement within ventricular muscle. Guidewire radial depth, between endocardial and epicardial surfaces, is ambiguous by x-ray and echocardiography. ObjectivesThe aim of this study was to develop a simple tool, EDEN (Electrocardiographic Radial Depth Navigation), to indicate radial depth during intramyocardial guidewire navigation. Combined with routine imaging, EDEN facilitates a new family of intramyocardial catheter procedures to slice, reshape, pace, and ablate the heart. MethodsWe mapped intramyocardial electrograms of left and right ventricular walls and septum during open- and closed-chest swine procedures (N = 53), including MIRTH (Myocardial Intramural Remodeling by Transvenous Tether) ventriculoplasty. We identified radial depth–dependent features on unipolar electrograms. We developed a machine learning–based classifier to indicate categorical position, and modeled the findings in silico to test understanding of the physiology. ResultsEDEN signatures distinguished 5 depth zones throughout left and right ventricular free walls and interventricular septum. Relative ST-segment elevation magnitude best discriminated position and was maximum (40.1 ± 6.5 mV) in the midmyocardium. Subendocardial positions exhibited dominant Q waves with lower-amplitude ST segments (16.8 ± 5.8 mV), whereas subepicardial positions exhibited dominant R waves with lower-amplitude ST segments (15.7 ± 4.8 mV). EDEN was unaffected by pacing-induced left bundle branch block. ST-segment elevation declined over minutes and reappeared after submillimeter guidewire manipulation. Modeling recapitulated EDEN features. The machine learning–based classifier was 97% accurate. EDEN successfully guided MIRTH ventriculoplasty. ConclusionsEDEN provides a simple and reproducible real-time reflection of categorical guidewire-tip radial depth during intramyocardial guidewire navigation. Used in tandem with x-ray, EDEN enables novel, transcatheter, intramyocardial therapies such as MIRTH, SESAME (Septal Surfing Along Midline Endocardium), and cerclage ventriculoplasty.

Abstract 28: Design Workshops: Participatory Co-Design and Iterative Adaptation of Cervical Cancer Screening Implementation Plans in Peru

Abstract Purpose: In many countries, implementation planning for delivery of cancer screening services functions as a ‘top-down’ process, often resulting in fragmentation and bottlenecks at points of service delivery. Participatory engagement of health system planners and actors from across cancer screening and treatment continuum involved with implementation, planning, and adaptation is hypothesized to lead to plans that have a higher likelihood of adoption and sustainability. We tested the feasibility of conducting a 4-day series of participatory ‘design workshops’ for implementation of the recently initiated HPV screening program in the DIRIS Lima Norte (DLN) region of Peru. Methods: The workshop agendas were co-designed by the Peruvian Ministry of Health (MINSA) and the National Cancer Institute (NCI) using principles of participatory action research, implementation science, and systems thinking. The workshop objectives were to clarify the goals and processes of the HPV cervical screening program and reflect on the initial implementation experience. Workshop design was attentive to a) building trust among the health system planners and actors, b) surfacing misconceptions and process bottlenecks, c) equitable representation of perspectives on the process from all levels of the screening system, and d) shared decision-making in actions to improve the system. Results: Through real-time participatory reflection and process mapping of the screening program, context-specific challenges were rapidly identified. The process maps helped participants gain a shared understanding of the complexity of the screening system and quickly identified how one part of the system can create barriers for proximal and distal parts of the system. Participants mentioned feeling detached from the distal barriers before the workshops but now understood their role in the decision-making and problem-solving processes and demonstrated a willingness to work with the regional director to implement process improvements in the system, specifically to ensure women testing positive received the appropriate follow-up care. Conclusion: Rapid embedded implementation research using facilitated workshops with broad health system representation to reflect on the processes and procedures was an acceptable quality improvement activity. MINSA plans to replicate this experience in other regions and to continue to create a culture of trust and establishment of learning health systems. Citation Format: Fatou Jallow, Andrea Matos Orbegozo, Maria Del Carmen Caruhapoma, Víctor A. Palacios, Milagros Montes, Carlos Santos, Margarita Correa-Mendez, Aubrey Villalobos, Alejandro Salicrup, Jose Jeronimo, Laura Nervi, Patti Gravitt, Julia Gage. Design Workshops: Participatory Co-Design and Iterative Adaptation of Cervical Cancer Screening Implementation Plans in Peru [abstract]. In: Proceedings of the 11th Annual Symposium on Global Cancer Research; Closing the Research-to-Implementation Gap; 2023 Apr 4-6. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(6_Suppl):Abstract nr 28.

Adaptive Reflection Detection and Control Strategy of Pointer Meters Based on YOLOv5s

Reflective phenomena often occur in the detecting process of pointer meters by inspection robots in complex environments, which can cause the failure of pointer meter readings. In this paper, an improved k-means clustering method for adaptive detection of pointer meter reflective areas and a robot pose control strategy to remove reflective areas are proposed based on deep learning. It mainly includes three steps: (1) YOLOv5s (You Only Look Once v5-small) deep learning network is used for real-time detection of pointer meters. The detected reflective pointer meters are preprocessed by using a perspective transformation. Then, the detection results and deep learning algorithm are combined with the perspective transformation. (2) Based on YUV (luminance-bandwidth-chrominance) color spatial information of collected pointer meter images, the fitting curve of the brightness component histogram and its peak and valley information is obtained. Then, the k-means algorithm is improved based on this information to adaptively determine its optimal clustering number and its initial clustering center. In addition, the reflection detection of pointer meter images is carried out based on the improved k-means clustering algorithm. (3) The robot pose control strategy, including its moving direction and distance, can be determined to eliminate the reflective areas. Finally, an inspection robot detection platform is built for experimental study on the performance of the proposed detection method. Experimental results show that the proposed method not only has good detection accuracy that achieves 0.809 but also has the shortest detection time, which is only 0.6392 s compared with other methods available in the literature. The main contribution of this paper is to provide a theoretical and technical reference to avoid circumferential reflection for inspection robots. It can adaptively and accurately detect reflective areas of pointer meters and can quickly remove them by controlling the movement of inspection robots. The proposed detection method has the potential application to realize real-time reflection detection and recognition of pointer meters for inspection robots in complex environments.

Integrating Distance Education into Mobile Devices Using Adobe Connect Pro

This article aims to promote Adobe Connect Pro on online learning as a discussion platform in an online class. Digitalization in higher education using digital learning platforms such as adobe connect pro is currently broadly used as educational media. In the research context, Adobe Connect Pro is utilized as a discussion platform in the online class. Digital learning Platform enables providers to deliver academic programs via digital learning platforms, facilitating communication and enabling knowledge preservation, selection, and distribution. Using a qualitative study, this article investigates how Adobe Connect Pro allows teacher trainers to collaborate by offering a forum for real-time reflection and debate on student-teacher video performance, which is a natural extension of a forum. The result of the observation shows that Adobe Acrobat Connect Pro’s online discussion forum promotes students’ learning interests and accommodates a variety of learners, including those with special needs who may find it challenging to be physically present in the traditional classroom all of the time or to keep up with the other students. It promotes inclusive learning by allowing anyone to learn at their own pace and schedule and freely participate in platform discussions. In conclusion, discussion forums using Adobe Acrobat Connect Pro have immense potential to push students to learn.

Real-time indirect glossy reflection based on linearly transformed spherical distributions

Real-time indirect glossy reflection based on linearly transformed spherical distributions